Age represents the main driver of surgical decision making in patients candidate to radical cystectomy.

BACKGROUND AND OBJECTIVES: Age might influence the choice of surgical approach, type of urinary diversion (UD) and lymph node dissection (LND) in patients candidate to radical cystectomy (RC) for urothelial bladder cancer (UBC). Similarly, age may enhance surgical morbidity and worsen perioperative outcomes. We tested the impact of age (octogenarian vs. younger patients) on surgical decision making and peri- and postoperative outcomes of RC. METHODS: Non-metastatic muscle-invasive UBC patients treated with RC at 18 high-volume European institutions between 2006 and 2021 were identified and stratified according to age (≥80 vs. <80 years). Intraoperative Complications Assessment and Reporting with Universal Standards and European Association of Urology guidelines recommendations were accomplished in collection and reporting of, respectively, intraoperative and postoperative complications. Multivariable logistic regression models (MVA) tested the impact of age on outcomes of interest. Sensitivity analyses after 1:3 propensity score matching were performed. RESULTS: Of 1955 overall patients, 251 (13%) were ≥80-year-old. Minimally invasive RC was performed in 18% and 40% of octogenarian and younger patients, respectively (p < 0.001). UD without bowel manipulation (ureterocutaneostomy, UCS) was performed in 31% and 7% of octogenarian and younger patients (p < 0.001). LND was delivered to 81% and 93% of octogenarian and younger patients (p < 0.001). At MVA, age ≥80 years independently predicted open approach (odds ratio [OR]: 1.55), UCS (OR: 3.70), and omission of LND (OR: 0.41; all p ≤ 0.02). Compared to their younger counterparts, octogenarian patients experienced higher rates of intraoperative (8% vs. 4%, p = 0.04) but not of postoperative complications (64% vs. 61%, p = 0.07). At MVA, age ≥80 years was not an independent predictor of length of stay, intraoperative or postoperative transfusions and complications, and readmissions (all p values >0.1). These results were replicated in sensitivity analyses. CONCLUSIONS: Age ≥80 years does not independently portend worse surgical outcomes for RC. However, octogenarians are unreasonably more likely to receive open approach and UCS diversion, and less likely to undergo LND.

Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network.

BACKGROUND: Important clinical information of patients is present in unstructured free-text fields of Electronic Health Records (EHRs). While this information can be extracted using clinical Natural Language Processing (cNLP), the recognition of negation modifiers represents an important challenge. A wide range of cNLP applications have been developed to detect the negation of medical entities in clinical free-text, however, effective solutions for languages other than English are scarce. This study aimed at developing a solution for negation recognition in Spanish EHRs based on a combination of a customized rule-based NegEx layer and a convolutional neural network (CNN). METHODS: Based on our previous experience in real world evidence (RWE) studies using information embedded in EHRs, negation recognition was simplified into a binary problem ('affirmative' vs. 'non-affirmative' class). For the NegEx layer, negation rules were obtained from a publicly available Spanish corpus and enriched with custom ones, whereby the CNN binary classifier was trained on EHRs annotated for clinical named entities (cNEs) and negation markers by medical doctors. RESULTS: The proposed negation recognition pipeline obtained precision, recall, and F1-score of 0.93, 0.94, and 0.94 for the 'affirmative' class, and 0.86, 0.84, and 0.85 for the 'non-affirmative' class, respectively. To validate the generalization capabilities of our methodology, we applied the negation recognition pipeline on EHRs (6,710 cNEs) from a different data source distribution than the training corpus and obtained consistent performance metrics for the 'affirmative' and 'non-affirmative' class (0.95, 0.97, and 0.96; and 0.90, 0.83, and 0.86 for precision, recall, and F1-score, respectively). Lastly, we evaluated the pipeline against two publicly available Spanish negation corpora, the IULA and NUBes, obtaining state-of-the-art metrics (1.00, 0.99, and 0.99; and 1.00, 0.93, and 0.96 for precision, recall, and F1-score, respectively). CONCLUSION: Negation recognition is a source of low precision in the retrieval of cNEs from EHRs' free-text. Combining a customized rule-based NegEx layer with a CNN binary classifier outperformed many other current approaches. RWE studies highly benefit from the correct recognition of negation as it reduces false positive detections of cNE which otherwise would undoubtedly reduce the credibility of cNLP systems.

MindReader: Unsupervised Classification of Electroencephalographic Data.

Electroencephalogram (EEG) interpretation plays a critical role in the clinical assessment of neurological conditions, most notably epilepsy. However, EEG recordings are typically analyzed manually by highly specialized and heavily trained personnel. Moreover, the low rate of capturing abnormal events during the procedure makes interpretation time-consuming, resource-hungry, and overall an expensive process. Automatic detection offers the potential to improve the quality of patient care by shortening the time to diagnosis, managing big data and optimizing the allocation of human resources towards precision medicine. Here, we present MindReader, a novel unsupervised machine-learning method comprised of the interplay between an autoencoder network, a hidden Markov model (HMM), and a generative component: after dividing the signal into overlapping frames and performing a fast Fourier transform, MindReader trains an autoencoder neural network for dimensionality reduction and compact representation of different frequency patterns for each frame. Next, we processed the temporal patterns using a HMM, while a third and generative component hypothesized and characterized the different phases that were then fed back to the HMM. MindReader then automatically generates labels that the physician can interpret as pathological and non-pathological phases, thus effectively reducing the search space for trained personnel. We evaluated MindReader's predictive performance on 686 recordings, encompassing more than 980 h from the publicly available Physionet database. Compared to manual annotations, MindReader identified 197 of 198 epileptic events (99.45%), and is, as such, a highly sensitive method, which is a prerequisite for clinical use.

Gold-Catalyzed 1,3-Thiazine Formation and Uncommon Tautomer Isolation.

This work represents the first example of a gold-catalyzed formation of 1,3-thiazine/1,3-thiazinane by means of a catalytic approach and further uncommon isolation of the two tautomers. The developed protocol gives rise to a broad scope of 1,3-thiazine derivatives with excellent yields in short reaction times. Interestingly, different isomers could be obtained depending on the state of the compound, and in the crystal state the 1,3-thiazinane isomer is obtained, while in solution the 1,3-thiazine is the unique isomer. This work represents an interesting approach for the synthesis of potential biologically relevant molecules and a crucial precedent in tautomerism isolation and characterization.

Correlates to psychological distress in frail older community-dwellers undergoing lockdown during the COVID-19 pandemic.

BACKGROUND: This study identifies correlates of the lockdown's psychological distress in frail older community-dwellers (Catalonia, Spain). METHODS: Participants from a community frailty intervention program, with a comprehensive geriatric assessment within the 12-months pre-lockdown and COVID-19 free during the first pandemic wave (March-May 2020), underwent a phone assessment past the lockdown to assess COVID-19-related emotional distress (DME) as well as other sociodemograhic, clinical and psychosocial factors. RESULTS: Of the 94 frail older adults (age = 82,34 ± 6,12 years; 68,1% women; 38,3% living alone), 84,9% were at risk of experiencing moderate-to-high psychological distress, according to the backward stepwise logistic regression model obtained (χ2 = 47,007, p < 0,001, Nagelkerke R2 = 0,528), based on the following factors: absence of depressive symptoms before lockdown (OR = 0,12, p = 0,014, 95%CI[0,023-0,647]), not carrying out leisure activities during lockdown (OR = 0,257, p = 0,023, 95%CI[0,079-0,832]) and currently experiencing high malaise due to COVID-19 situation (OR = 1,504, p < 0,001, 95%CI[1,241-1,822]). DISCUSSION: These findings suggest that it is necessary to favour a prior overall health status and to empower frail older community-dwellers in the use of a broad repertoire of coping strategies in the face of adversity to foster mental health and keep at bay the potential emotional impact of the situation generated by the COVID pandemic.

Assessment of Water Quality Parameters and their Seasonal Behaviour in a Portuguese Water Supply System: a 6-year Monitoring Study.

Water quality monitoring is a fundamental tool in the management of freshwater resources. The purpose of monitoring is to provide meaningful quality data for local action planning and catchment-wide decision making. The assessment of water quality is crucial to guarantee the efficient operation of the Water Treatment Plants (WTPs), promoting health conditions and contributing for a more sustainable urban water cycle. In accordance, the objective of this study was to evaluate key target chemical and microbiological water quality parameters, some of them already monitored within Portuguese/EU legal framework and others still not regulated, but with environmental and human heath relevance. A local monitoring database model, using a 6-year period (from 2014 to 2019) of water quality data, regarding water samples collected on representative sampling locations covering the freshwater abstraction sites, conventional WTPs and distribution network was assessed. This work provides new knowledge regarding occurrence and seasonal behaviour for both microbiological and chemical water quality parameters, essential to understand/manage the water supply system. Additionally, relationships between the target variables were also assessed. Particularly, strong correlations were identified between TOC and THMs formation at distribution network (r = 0.69; p ≤ 0.001); nitrates were the water quality parameter that revealed the best correlation between surface water source and treated water (r = 0.81; p ≤ 0.001), suggesting that treatment yield/performance is dependent on surface water load. The local and continuous monitoring of water systems are crucial to implement new approaches to guarantee the best quality of drinking water throughout the supply system.

From Thioureas to Thioquinolines through Isolated Benzothiazines by Gold Catalysis.

New benzothiazine heterocycles have been formed from thiourea derivatives by using different gold catalysts. The catalyst and the conditions were optimised towards the selective synthesis of six-membered benzothiazine heterocycles, characterised by X-ray diffraction. Interestingly, these organic compounds evolved under gold catalysis in basic medium to achieve the formation of amino thioquinolines through an unprecedented aromatisation process of the heterocycle. The reaction was also carried out stoichiometrically by reaction with gold complexes to afford thioquinolines coordinated to the gold fragment. Benzothiazine, amino thioquinoline heterocycles and gold-derived species have a great potential for biological applications.

Whole-genome comparison of endogenous retrovirus segregation across wild and domestic host species populations.

Although recent advances in sequencing and computational analyses have facilitated use of endogenous retroviruses (ERVs) for deciphering coevolution among retroviruses and their hosts, sampling effects from different host populations present major challenges. Here we utilize available whole-genome data from wild and domesticated European rabbit (Oryctolagus cuniculus sp.) populations, sequenced as DNA pools by paired-end Illumina technology, for identifying segregating reference as well as nonreference ERV loci, to reveal their variation along the host phylogeny and domestication history. To produce new viruses, retroviruses must insert a proviral DNA copy into the host nuclear DNA. Occasional proviral insertions into the host germline have been passed down through generations as inherited ERVs during millions of years. These ERVs represent retroviruses that were active at the time of infection and thus present a remarkable record of historical virus-host associations. To examine segregating ERVs in host populations, we apply a reference library search strategy for anchoring ERV-associated short-sequence read pairs from pooled whole-genome sequences to reference genome assembly positions. We show that most ERVs segregate along host phylogeny but also uncover radiation of some ERVs, identified as segregating loci among wild and domestic rabbits. The study targets pertinent issues regarding genome sampling when examining virus-host evolution from the genomic ERV record and offers improved scope regarding common strategies for single-nucleotide variant analyses in host population comparative genomics.

Shigella IpaA mediates actin bundling through diffusible vinculin oligomers with activation imprint.

Upon activation, vinculin reinforces cytoskeletal anchorage during cell adhesion. Activating ligands classically disrupt intramolecular interactions between the vinculin head and tail domains that bind to actin filaments. Here, we show that Shigella IpaA triggers major allosteric changes in the head domain, leading to vinculin homo-oligomerization. Through the cooperative binding of its three vinculin-binding sites (VBSs), IpaA induces a striking reorientation of the D1 and D2 head subdomains associated with vinculin oligomerization. IpaA thus acts as a catalyst producing vinculin clusters that bundle actin at a distance from the activation site and trigger the formation of highly stable adhesions resisting the action of actin relaxing drugs. Unlike canonical activation, vinculin homo-oligomers induced by IpaA appear to keep a persistent imprint of the activated state in addition to their bundling activity, accounting for stable cell adhesion independent of force transduction and relevant to bacterial invasion.

Rennet-Induced Casein Micelle Aggregation Models: A Review.

Two phases are generally recognized in the enzymatic coagulation of milk: hydrolysis and aggregation, although nowadays more and more researchers consider the non-enzymatic phase to actually be a stage of gel formation made up of two sub-stages: micellar aggregation and hardening of the three-dimensional network of para-κ-casein. To evaluate this controversy, the main descriptive models have been reviewed. Most of them can only model micellar aggregation, without modeling the hardening stage. Some are not generalizable enough. However, more recent models have been proposed, applicable to a wide range of conditions, which could differentiate both substages. Manufacturing quality enzymatic cheeses in a cost-effective and consistent manner requires effective control of coagulation, which implies studying the non-enzymatic sub-stages of coagulation separately, as numerous studies require specific measurement methods for each of them. Some authors have recently reviewed the micellar aggregation models, but without differentiating it from hardening. Therefore, a review of the proposed models is necessary, as coagulation cannot be controlled without knowing its mechanisms and the stages that constitute it.